With rapid improvements in both hardware and software technologies, large collections of images are available on networks such as the Web. End-users typically use web search engines to search the hundreds of million of images available on the Web for image(s) of interest. An end-user typically submits an image search according to information needs, which can be categorized with respect to a navigational, informational, or transactional context. A search submitted with respect to a navigational context is directed to locating a specific web resource. A search submitted with respect to an informational context, typically considered to most frequent type of search performed by users, is directed to a task of locating information about a particular topic or obtaining an answer to an open-ended question. A search submitted with respect to a transactional context is directed to performing a web-mediated activity such as software downloading, online shopping and checking e-mail.
Web image search results are typically presented to an end-user in a simple ranked list. Ranked lists are not conducive to browsing search results, especially when the image search is responsive to an informational search. In such a scenario, image(s) presented in a first page are typically not more relevant to the search query than image(s) associated with any following search result pages. As a result, end-users typically spend substantial amounts of time and energy navigating through web image search results to find one or more images of interest. Moreover, if the user wants to compare different search results using such a ranked-list, the user will typically need to sequentially scan the resulting images, one after another to find an image of interest, while devoting considerable efforts in page navigations.